ABSTRACT Objectives Hyperuricemia and gout are common but underappreciated comorbidities in Type 2 diabetes (T2D), obesity and chronic kidney disease (CKD). We aimed to quantify the pooled effects of glucagon‐like peptide‐1 receptor agonists (GLP‐1 RAs) and dual glucose‐dependent insulinotropic polypeptide (GIP)/GLP‐1 receptor agonists on serum uric acid (SUA), incident gout and hyperuricemia, and to determine whether these effects vary by drug class and are mediated by weight loss. Methods We searched PubMed/MEDLINE, Embase, CENTRAL and ClinicalTrials.gov through July 2026 for RCTs of ≥ 12 weeks' duration reporting SUA change, gout flares or hyperuricemia incidence. Random‐effects meta‐analysis, subgroup and sensitivity analyses and meta‐regression were performed. Registered with PROSPERO (CRD420261468511). Results Eighteen RCTs (77 942 participants) met inclusion criteria. Incretin‐based therapy significantly reduced SUA versus control (weighted mean difference [WMD] −0.44 mg/dL, 95% CI −0.52 to −0.35), reduced incident gout flares (hazard ratio [HR] 0.62, 95% CI 0.53–0.72), and reduced hyperuricemia incidence (odds ratio [OR] 0.61, 95% CI 0.53–0.70). Dual GIP/GLP‐1 RA (tirzepatide) produced greater SUA lowering than mono GLP‐1 RAs (−0.62 vs. −0.35 mg/dL, p = 0.001). Body‐weight loss was a significant moderator of SUA reduction ( β = −0.041 mg/dL per kg, p < 0.001), explaining 84.7% of between‐trial heterogeneity, with a significant weight‐independent intercept (−0.19 mg/dL, p < 0.001). The SUA reduction was robust in all sensitivity analyses, including restriction to placebo‐controlled trials. GRADE certainty was high for SUA and moderate for gout flares (owing to small‐study effects) and hyperuricemia incidence. Conclusion Incretin‐based therapies were associated with modest reductions in SUA and with a lower incidence of gout flares and hyperuricemia, an effect largely related to weight loss. The clinical relevance of these effects, and the mechanism of any weight‐independent component, remains uncertain and warrant confirmation in dedicated trials.
ABSTRACT Aims Finerenone was approved in China in 2022 for adult patients with chronic kidney disease (CKD) associated with Type 2 diabetes (T2D). This study aimed to characterize Chinese patients with CKD and T2D who initiated finerenone in routine clinical practice and to evaluate treatment outcomes. Materials and Methods This retrospective study used electronic health records from Tianjin, China, and included adult patients with CKD and T2D who initiated finerenone between January 2023 and December 2024. Baseline characteristics were summarized. Relative changes in urinary albumin‐to‐creatinine ratio (UACR), estimated glomerular filtration rate (eGFR) and serum potassium were assessed. Recorded hyperkalaemia events were evaluated during follow‐up. Key outcomes were examined in the overall cohort and across subgroups. Results A total of 6537 patients were included (66.4% male; mean age 57.6 years). Of these, 97.0% with baseline UACR and eGFR values were categorized as moderate, high, or very high Kidney Disease: Improving Global Outcomes (KDIGO) risk categories. At Month 4, median UACR decreased substantially by 40.7% (95% confidence interval [CI]: 32.2%, 49.1%), the mean eGFR declined slightly by 3.2% (95% CI: 2.4%, 4.0%) and the mean serum potassium increased by 4.6% (95% CI: 3.9%, 5.3%). These trends were generally consistent across subgroups. The incidence rate of hyperkalaemia events was 4.1 per 100 person‐years. Conclusions Patients with CKD and T2D who initiated finerenone experienced a substantial reduction in UACR, a slight decrease in eGFR, and were generally well tolerated during follow‐up. These findings reinforce the effectiveness and safety of finerenone in Chinese real‐world clinical practice.
ABSTRACT Aims We evaluated the relationship between metformin, one of the most commonly prescribed medications for individuals with diabetes, and COVID‐19 sequelae. Materials and Methods We evaluated a retrospective cohort of individuals in the National Clinical Cohort Collaborative with Type 2 diabetes mellitus and COVID‐19 who were prescribed metformin or a dipeptidyl peptidase‐4 inhibitor (DPP4i) at least 30 days before the onset of acute COVID‐19 between 1 October 2021, and 15 November 2023. We compared the 12‐month cumulative incidence of Long COVID diagnosis (ICD‐10 U09.9: Post COVID‐19 condition, unspecified), probable Long COVID (based on a model‐derived phenotype), and mortality between individuals prescribed metformin versus DPP4i. We applied Super Learner and targeted maximum likelihood estimation to obtain risk ratios while adjusting for covariates of interest. Results In our sample of 53 332 individuals with Type 2 diabetes and COVID‐19, we found that metformin prescription was associated with a lower risk of all‐cause mortality after COVID‐19 (adjusted risk ratio [aRR]: 0.61, 95% CI: 0.51, 0.73). We also observed that metformin users, compared to DPP4i users, had a slightly lower risk of probable Long COVID (aRR: 0.87, 95% CI: 0.81, 0.94) but did not detect a significant relationship with the clinically defined outcome of Long COVID diagnosis (aRR: 0.90, 95% CI: 0.68, 1.20). Conclusions These findings support the hypothesis that metformin prescription during acute COVID‐19 may be associated with lower mortality among adults with diabetes.
ABSTRACT Aim The glucose management indicator (GMI) estimates HbA1c from continuous glucose monitoring (CGM)‐derived mean glucose. We assessed whether this relationship differs between contemporary CGM systems. Materials and Methods In this observational study, mean sensor glucose was derived from 2 months of CGM data preceding HbA1c measurement in adults with Type 1 diabetes using Dexcom (Dx) G6/G7 ( n = 252) or Medtronic Guardian 4/Simplera (GSi) ( n = 180). Device‐specific GMI equations were derived using linear regression of measured HbA1c on mean sensor glucose and compared with the original GMI equation. For direct comparison of the Dx and GSi GMI equations, these GMI equations were combined, with 95% confidence intervals calculated using the delta method. Results The Dx GMI equation yielded statistically significantly lower GMI values compared with the original GMI equation at mean sensor glucose levels < 13.7 mmol/L, with increasing differences at lower glucose levels. Conversely, at mean sensor glucose levels above 8.3 mmol/L, the GSi GMI equation yielded statistically significantly higher GMI values than the original GMI equation, with increasing differences at higher glucose levels. The Dx and GSi device‐specific GMI equations yielded statistically significantly different GMI values > 6.7 mmol/L, with increasing differences at higher glucose levels. Conclusions The relationship between mean sensor glucose and HbA1c differed between contemporary CGM systems. This finding suggests that device‐specific GMI equations may improve interpretation of glycaemic control in the absence of standardisation across contemporary CGM systems.
